Attribute Information:

The dataset includes 9 columns with information on 800 people.

  1. age : in years
  2. weight : body weight in pounds (lbs)
  3. bmi : Body Mass Index (weight in kg/(height in m)2)
  4. blood_pressure : resting blood pressure (mm Hg)
  5. insulin_test : inuslin test value
  6. liver_stress_test : liver_stress_test value
  7. cardio_stress_test : cardio_stress_test value
  8. years_smoking : number of years of smoking
  9. zeta_disease :
          1 = yes;
          0 = no

Lets apply different machine learning models

  1. Logistic Regression
  2. SVM
  3. Random Forests
  4. Decision Tree
  5. Navie Baye's
  6. KNeighborsClassifier
  7. AdaBoost
  8. XGBoost

Creating Instances

PreTune with Default parameter

PostTune with Best parameters

Learning curve